Abstract

Himalayas the “roof of the world” are the source of water supply for major South Asian Rivers and fulfill the demand of almost one sixth of world’s humanity. Hydrological modeling poses a big challenge for Himalayan River Basins due to complex topography, climatology and lack of quality input data. In this study, hydrological uncertainties arising due to remotely sensed inputs, input resolution and model structure has been highlighted for a Himalayan Gandak River Basin.
Firstly, spatial input DEM (Digital Elevation Model) from two sources SRTM (Shuttle Radar Topography Mission) and ASTER (Advanced Space borne Thermal Emission and Reflection Radiometer) with resolutions 30m, 90m and 30m respectively has been evaluated for their delineation accuracy. The result reveals that SRTM 90m has best performance in terms of least area delineation error (13239.28 km2) and least stream network delineation error.
The daily satellite precipitation estimates TRMM 3B42 V7 (Tropical Rainfall Monitoring Mission) and CMORPH (Climate Prediction Center MORPHing Technique) are evaluated for their feasibly over these terrains. Evaluation based on various scores related to visual verification method, Yes/no dichotomous, and continuous variable verification method reveal that TRMM 3B42 V7 has better scores than CMORPH.
The effect of DEM resolution on the SWAT (Soil Water Assessment Tool) model outputs has been demonstrated using sixteen DEM grid sizes (40m-1000m). The analysis reveals that sediment and flow are greatly affected by the DEM resolutions (for DEMs>300m). The amount of total nitrogen (TN) and total phosphorous (TP) are found affected via slope and volume of flow for DEM grid size ≥150m. The T-test results are significant for SWAT outputs for grid size >500m at a yearly time step.
The SWAT model is accessed for uncertainty during various hydrological processes modeling with different setups/structure. The results reflects that the use of elevation band modeling routine (with six to eight elevation bands) improves the streamflow statistics and water budgets from upstream to downstream gauging sites. Also, the SWAT model represents a consistent pattern of spatiotemporal snow cover dynamics when compared with MODIS data.
At the end, the uncertainty in the stream flow simulation for TRMM 3B42 V7 for various rainfall intensity has been accessed with the statistics Percentage Bias (PBIAS) and RSR (RMSE-observations Standard Deviation Ratio). The results found that TRMM simulated streamflow is suitable for moderate (7.5 to 35.4 mm/day) to heavy rainfall intensities (35.5 to 124.4 mm/day). The finding of the present work can be useful for TRMM based studies for water resources management over the similar parts of the world.